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A method for calling gains and losses in array CGH data.

Pei Wang·Young Kim·Jonathan Pollack·Balasubramanian Narasimhan·Robert Tibshirani
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Abstract

Array CGH is a powerful technique for genomic studies of cancer. It enables one to carry out genome-wide screening for regions of genetic alterations, such as chromosome gains and losses, or localized amplifications and deletions. In this paper, we propose a new algorithm 'Cluster along chromosomes' (CLAC) for the analysis of array CGH data. CLAC builds hierarchical clustering-style trees along each chromosome arm (or chromosome), and then selects the 'interesting' clusters by controlling the False Discovery Rate (FDR) at a certain level. In addition, it provides a consensus summary across a set of arrays, as well as an estimate of the corresponding FDR. We illustrate the method using an application of CLAC on a lung cancer microarray CGH data set as well as a BAC array CGH data set of aneuploid cell strains.

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AlgorithmsChromosome AberrationsCluster AnalysisGene DosageGenome, HumanHumansLung NeoplasmsNucleic Acid HybridizationOligonucleotide Array Sequence AnalysisJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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Pei Wang, Young Kim, Jonathan Pollack, Balasubramanian Narasimhan, Robert Tibshirani. 2005. A method for calling gains and losses in array CGH data.. https://doi.org/10.1093/biostatistics%2Fkxh017

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